Using probabilistic neural networks for modeling metal fatigue and random vibration in process pipework
Author | Nashed, Mohamad Shadi |
Author | Mohamed, M Shadi |
Author | Shady, Omar Tawfik |
Author | Renno, Jamil |
Available date | 2024-06-02T06:20:08Z |
Publication Date | 2022 |
Publication Name | Fatigue and Fracture of Engineering Materials and Structures |
Resource | Scopus |
Identifier | http://dx.doi.org/10.1111/ffe.13660 |
ISSN | 8756758X |
Abstract | Many experiments are usually needed to quantify probabilistic fatigue behavior in metals. Previous attempts used separate artificial neural network (ANN) to calculate different probabilistic ranges which can be computationally demanding for building probabilistic fatigue constant life diagram (CLD). Alternatively, we propose using probabilistic neural network (PNNs) which can capture data distribution parameters. The resulted model is generative and can quantify aleatoric uncertainty using a single network. Two tests are presented. The first captures the fatigue life aleatoric uncertainty for P355NL1 steel and successfully builds a probabilistic fatigue CLD. The resulted network is not only more efficient but also provides higher accuracy compared with ANN. To assess fatigue, the second test examines vibrations of a pipework assembly. The proposed methodology quantifies the nonlinear relation between the vibration velocity and the equivalent stress and successfully reflects measurements uncertainties in fatigue assessment. The proposed methodology is published in opensource format (https://github.com/MShadiNashed/probabilistic-machine-learning-for-fatigue-data). |
Sponsor | This project was graciously sponsored by the Qatar National Research Fund (a member of Qatar Foundation) via the National Priorities Research Project under grant NPRP-11S-1220-170112. |
Language | en |
Publisher | John Wiley and Sons Inc |
Subject | artificial neural network (ANN) failure probability fatigue fatigue life prediction probabilistic method vibration |
Type | Article |
Pagination | 1227-1242 |
Issue Number | 4 |
Volume Number | 45 |
Files in this item
Files | Size | Format | View |
---|---|---|---|
There are no files associated with this item. |
This item appears in the following Collection(s)
-
Mechanical & Industrial Engineering [1343 items ]